<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Caeiro, Frederico</style></author><author><style face="normal" font="default" size="100%">Martins,Ana P.</style></author><author><style face="normal" font="default" size="100%">Sequeira,Inês J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Maximum likelihood estimator</style></keyword><keyword><style  face="normal" font="default" size="100%">Moment estimator</style></keyword><keyword><style  face="normal" font="default" size="100%">Monte-Carlo method</style></keyword><keyword><style  face="normal" font="default" size="100%">Pareto distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantile regression estimator</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015/3/10</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.scopus.com/inward/record.url?scp=84939648344&amp;partnerID=8YFLogxK</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">American Institute of Physics Inc.</style></publisher><volume><style face="normal" font="default" size="100%">1648</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.&lt;/p&gt;
</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;sem pdf conforme despacho&lt;/p&gt;
</style></notes><custom2><style face="normal" font="default" size="100%">10.1063/1.4912753</style></custom2></record></records></xml>